Artificial Intelligence Techniques for Monitoring Carbon Emissions and Supporting Green Investment Decisions

Abstract

Artificial Intelligence (AI) has been introduced as a revolutionary tool for carbon emission monitoring, and helps in making investment decisions that are both environmentally friendly and sustainable. The systematic review summarises the existing evidence regarding AI applications in estimating carbon emissions, using Measurement, Reporting and Verification (MRV) schemes and their incorporation into Environmental, Social and Governance (ESG) ratings, as well as green finance programs. The systematic review included 55 studies that were published between 2021 and 2025 in the industrial, energy, transportation, agricultural, and multisectoral contexts. It is shown that machine-learning, deep-learning, and hybrid algorithms are significantly more effective in enhancing the accuracy of emission estimation, promoting close to real-time monitoring, and helping locate hotspots of emissions. The review also clarifies how AI-derived insights can help to both inform ESG reporting and make climate-aligned investment decisions, and facilitate regulatory compliance. However, there are ongoing issues of data quality shortages, poor model interpretability, barriers to the estimation of Scope 3 emissions, and now disparities in technological access. The paper highlights the strategic importance of AI in the context of filling the gap between environmental monitoring and sustainable finance, providing researchers, investors, and policymakers with evidence-based suggestions to increase their pace of decarbonisation in the world.